CATCHING THE SUGARS: ELECTROCHEMICAL APTASENSORS FOR THE DETECTION OF CANCER-RELATED GLYCOSYLATION CHANGES IN PROSTATE SPECIFIC ANTIGEN

Cancer is associated with aberrant glycosylation and each type is characterized by a distinct change in the glycan structure. Therefore, analysis of tumor-linked glycan alterations is proposed as a valuable tool for cancer diagnosis. The glycosylation profile is currently characterized by long and complicated protocols, based on final MS detection or the use of lectins. However, these procedures cannot be applied for routine analysis in early detection of cancer and there is a clear need for new methods. Aptamers can be tailored to specifically detect glycosylation and their use as synthetic receptors appears to be a promising approach to replace the current methods . In the case of prostate cancer, it has been recently described that there is a variation in the fucose and the sialic acid of Prostate Specific Antigen (PSA).

We present two strategies to direct the selection of aptamers towards the glycans of PSA. The SELEX procedure is based on counter-selection steps against recombinant PSA and the use of lectins. Aptamers in the last cycle are cloned, sequenced and classified into families using bioinformatic tools. The most abundant aptamers are characterized by electrochemical binding assays. Two aptamers were obtained with different binding characteristics: ability to recognize glycans of any glycoprotein and to specifically recognize the glycans of PSA due to the interaction with amino acids of the protein.

We employ the selected aptamers and an aptamer previously described for the development of electrochemical aptasensors, based on sandwich or direct label-free assays. Both aptasensors respond to different levels of PSA in human serum and are applied to the analysis of serum samples. The results point to the detection of glycans as an alternative for the detection of prostate cancer, with potential to improve clinical outcomes of current PSA tests, which would reduce the number of unnecessary biopsies.